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PhD Daytime (Digital Lifecycle Twins for Predictive Maintenance) (V32.3638)

PhD Daytime (Digital Lifecycle Twins for Predictive Maintenance)

We are looking for a PhD at the Department of Computer Science and Mathematics of the Eindhoven University of Technology, the Netherlands in the fields of machine learning, knowledge mining & management and/or natural language processing. The PhD student will work on the DayTime project.
Department of Mathematics & Computer Science
Data Science Center Eindhoven
Date off
Reference number

Job description

Project description
Daytime stands for Digital Lifecycle Twins for Predictive Maintenance. The objective of the Daytime `project is to demonstrate the applicability of Industry 4.0 and in particular DayTime innovations beyond traditional productions plants into the hospitals and the home by treating healthcare equipment as means or tools for production.

Healthcare encompasses both capital intensive equipment in hospitals and smart consumer products at homes. In either case reliable mapping of user interaction into system response is crucial in supporting the customer to optimally operate the product. DayTime will enable manufacturers to transform into digital service provides giving advice tailored to the user. This advice will be based on actual system status and usage combining digital twin concepts with user/usage profiling. The advice encompasses suggestions to improve performance, reduce wear and tear and provide instructions to improve longevity or pro-actively deliver maintenance as service.

The TU/e will focus on knowledge valorization by creating and translating research results into successful innovations, working together with the consortium partners, especially with Philips Research and Philips Magnetic Resonance business on the topics of predictive and reactive maintenance by applying data science and artificial intelligence technologies.

 An extensive project description is available on request.

Tasks of the PhD student:

  • carry out research within the project, in cooperation with the other parties involved;
  • report on the results in project deliverables, papers and conference contributions;
  • a small contribution to the teaching activities of the Computer Science Faculty may be asked.

Job requirements

We are looking for a candidate who meets the following requirements:

  • A master’s degree (or an equivalent university degree)  in computer science, information science or related fields (mathematics or electrical engineering);
  • A research oriented attitude;
  • Experience in at least one of the following areas: NLP, text mining, machine learning, and knowledge management
  • Solid programing skills (e.g. java)
  • Knowledge of Phyton, R Tensorflow, or similar languages and tools is a plus;
  • Ability to work in a team, interest in collaborating with the industrial partners;
  • Fluent in spoken and written English.

Conditions of employment

We offer:

  •  A full-time temporary appointment for 4 years;
  • Salary in accordance with CAO of the Dutch universities;
  • Support for your personal development and career planning including courses, summer schools, conference visits etc.;
  • An extensive package of fringe benefits, including excellent technical infrastructure, child care, savings schemes, and excellent sports facilities, extra holiday allowance (8%, May), and end-of-year bonus (8.3%, December);
  • Foreign applicants may benefit from the 30% tax regulation in order to get a higher net salary, when granted.

Information and application


For more information about the project, please contact Prof. dr. Milan Petkovic, e-mail: m.petkovic [at]

For information about employment conditions please contact Human Resources at TU/e, e-mail: pzwin [at]


The application should consist of the following parts:

  • Cover letter explaining your motivation and qualifications for the position;
  • Detailed Curriculum Vitae;
  • List of courses taken at the Bachelor and Master level including marks;
  • List of publications and software artifacts developed;
  • Proof of English language skills (if applicable)

Please apply by using the 'Apply for this job button'. A maximum of 5 documents of 2 MB each can be uploaded. If necessary please combine documents.

You can apply by using the 'Apply for this job' button on top of this page.